Cybersecurity with Ai or Cloud Security Engineer

MUFG
Jersey City, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Jersey City, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Software System Penetration Testing
Cloud Computing Security
Computer Security
Continuous Integration
Information Leak Prevention
DevOps
Identity and Access Management
Machine Learning
Open Web Application Security
Systems Development Life Cycle
Azure
Software Vulnerability Management
Data Logging
Microsoft Power Automate
Spring Cloud
Large Language Models
Software Security
Generative AI
Infrastructure as Code (IaC)
Amazon Web Services (AWS)
AI Platforms
Kubernetes
Terraform
Devsecops
Software Library
Docker
Vulnerability Analysis
Microservices

Job description

MUFG Union Bank is looking for an experienced AI/ML Security Engineer to join its AI Platform team in Jersey City, NJ. This role is responsible for securing enterprise AI/ML and Generative AI platforms by implementing robust cloud security, DevSecOps, AI risk management, and compliance controls. The ideal candidate will have strong expertise in AWS security, Infrastructure as Code (Terraform), Kubernetes, CI/CD security, and AI-specific security threats such as prompt injection, adversarial attacks, secure RAG, and model supply chain risks., · Design and implement security architecture for AI/ML platforms, LLM applications, RAG pipelines, and agentic AI systems.

· Perform threat modeling for AI-specific risks including prompt injection, jailbreak attacks, adversarial ML, retrieval poisoning, model inversion, and data leakage.

· Secure AWS cloud infrastructure using IAM, KMS, Secrets Manager, VPC security, encryption, logging, and monitoring.

· Integrate security controls into DevSecOps pipelines, CI/CD workflows, Kubernetes, Docker, and Terraform-based Infrastructure as Code.

· Review AI models, APIs, open-source libraries, and third-party AI services for security, privacy, and compliance risks.

· Implement secure access controls, least privilege policies, API security, and data protection mechanisms.

· Conduct vulnerability assessments, AI red teaming, penetration testing, and production security reviews.

· Build monitoring, alerting, and logging for AI applications to detect anomalous behavior, policy violations, and data leakage.

· Collaborate with AI engineers, cloud architects, and DevOps teams to implement enterprise security controls.

· Maintain security documentation, audit evidence, compliance reports, and risk assessments.

Requirements

· 8+ years of experience in Cybersecurity, Cloud Security, Application Security, or DevSecOps.

· Strong hands-on experience with AWS Security (IAM, KMS, VPC, CloudTrail, GuardDuty, Secrets Manager, Encryption).

· Experience securing Kubernetes, Docker, Microservices, APIs, and cloud-native applications.

· Strong experience with Terraform and Infrastructure as Code (IaC).

· Experience implementing security in CI/CD pipelines and DevSecOps environments.

· Strong AWS cloud security exposure or comparable hyperscaler security depth, including IAM, encryption, network controls, logging, secrets, and secure deployment patterns.

· Knowledge of AI/ML and Generative AI security concepts including:

o Prompt Injection

o AI Red Teaming

o Adversarial Machine Learning

o Secure RAG

o Model Supply Chain Security

o Data Leakage Prevention

o Model Misuse

o Retrieval Poisoning

· Experience with vulnerability management, threat modeling, secure SDLC, incident response, and security testing.

· Excellent understanding of cloud security architecture and enterprise security best practices.

· Strong communication and stakeholder management skills.

Preferred Qualifications

· Experience securing enterprise AI/ML or Generative AI platforms in production.

· Financial Services or Banking domain experience.

· Experience with AI Governance, Privacy, Compliance, and Regulatory standards.

· Knowledge of Power Platform Security, Microsoft Copilot Studio Governance, and Data Loss Prevention (DLP).

· Familiarity with AI security frameworks such as OWASP Top 10 for LLMs, NIST AI RMF, and MITRE ATLAS.

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